Automatic closed edge detection using level lines selection

Thomas Hurtut (1) , Farida Cheriet (1)

1 LIV4D - Laboratoire d'Imagerie et de Vision 4D

This paper presents a closed edge detection method based on a level lines selection approach. The proposed method is based on an unsupervised probabilistic scheme using an a contrario method. A level line is considered meaningful if its contrast and length is unlikely to be due to chance. Besides being unsupervised, this method exploits a tree structure. The first step of the proposed approach is to reduce the meaningful level lines set using this hierarchical structure. Compared with a previous method using the same principle, our method achieve a 67% reduction rate of irrelevant levels lines. The second step of the proposed approach illustrates the high flexibility of using closed edge boundaries such as levels lines. Using a rather simple curvature analysis, the proposed method detects anatomical structures boundaries from CT scan images.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Thomas Hurtut, Farida Cheriet. Automatic closed edge detection using level lines selection. International Conference on Image Analysis and Recognition, 2007, Canada. pp.187-197. ⟨hal-00430458⟩